Systems and methods for computer modeling and visualizing entity attributes

Abstract

At least one processor configured to perform operations including receiving data from a plurality of disparate data sources, the data including a plurality of variables associated a plurality of entities and characteristics of the entities; extracting one or more associations from the data, wherein each of the one or more associations includes one or more probabilistic distributions based on a relationship between the performance metrics and the entities and their positions; generating, based on the associations, a flight index for each of the entities; wherein the flight index is a statistical measure of a likelihood that an entity will leave the organization; generating a performance index to each of the entities; identifying, based on a comparison between the flight index and the performance index, a flight probability the entities being higher than a threshold flight probability; implementing, based on the identification, policy changes in the organization.

1 . A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to perform operations comprising:
 receiving data from a plurality of disparate data sources, the data including a first and second plurality of variables;
 wherein a first plurality of variables is associated with one entity of a plurality of entities in a position of a plurality of positions; 
 wherein a second plurality of variables is associated with a performance metric of a plurality of performance metrics associated with the each of the plurality of entities; 
 wherein the plurality of disparate data sources includes at least one of: one or more input datasets, one or more second input datasets, individual performance monitoring, team monitoring, and market monitoring; 
   generating a plurality of indexes, where the plurality of indexes comprises:
 a first index associated with the plurality of positions; 
 a second index associated with the plurality of entities; 
 a third index associated with one or more characteristics associated with each of the plurality of entities; and 
 a fourth index associated with the plurality of performance metrics; 
   storing the plurality of indexes in a database;   extracting one or more associations from the plurality of indexes, wherein each of the one or more associations includes one or more probabilistic distributions based on a relationship between each of the plurality of performance metrics and each of the plurality of positions;   generating, based on each of the plurality of entities, the associated performance metrics, and the extracted one or more associations, a flight index for each of the entities;
 wherein the flight index is a statistical measure of a likelihood that the associated entity will change from the associated entity's current position within an organization to one or more new positions outside of the organization; 
   generating, based on each of the plurality of entities and the associated performance metrics, a performance index to each of the entities;   comparing the flight index for each of the entities with the performance index of the same entity; and   identifying, based on the comparison, a flight probability of one or more chosen entities of the plurality of entities being higher than a threshold flight probability;   implementing, based on the identification, one or more changes to one or more policies of the organization;
 wherein the one or more changes to one or more policies are configured to reduce the statistical likelihood that the one or more chosen entities will change from a current positions of the one or more chosen entities current position within the organization to one or more new positions outside of the organization; and 
   monitoring, based on the implementation, the flight index of the one or more chosen entities over a period of time.   
     
     
         2 . The non-transitory computer readable medium of  claim 1 , the extracting the one or more associations further comprises:
 identifying one or more indicia related to the at least one of: one or more input datasets, one or more second input datasets, individual performance monitoring, team monitoring, and market monitoring; and   wherein the one or more indicia are associated historical conditions related to employee turnover.   
     
     
         3 . The non-transitory computer readable medium of  claim 1 , the operations further comprising:
 creating a distribution of flight probability for each of the plurality of positions, wherein the distribution uses the flight index for each entity of the plurality of entities; and   generating, using the distribution, a quantity of identified entities having a flight index higher than a threshold flight probability in each of the plurality of positions over a duration of time; and   extracting, based on the generation and the third index, a characteristic flight probability metric.   
     
     
         4 . The non-transitory computer readable medium of  claim 3 , the operations further comprising generating a visualization of the distribution. 
     
     
         5 . The non-transitory computer readable medium of  claim 1 , the operations further comprising:
 generating a graphical user interface containing information entry fields for receiving user input regarding input datasets;   providing the graphical user interface for display on a user device;   receiving, from the graphical user interface via the user device, the one or more input datasets; and   generating the third index based on the one or more input datasets.   
     
     
         6 . The non-transitory computer readable medium of  claim 5 , the operations further comprising:
 receiving, from communications between each of the plurality of entities, the one or more input second datasets; and   generating the third index based on the one or more second input datasets.   
     
     
         7 . The non-transitory computer readable medium of  claim 1 , wherein the one or more characteristics of the third index includes one or more of the following: commute time, years in an associated position in an organization, time spent at team building events, messages sent within the organization, age, gender, race, sexual orientation, and marital status. 
     
     
         8 . A method comprising:
 receiving data from a plurality of disparate data sources, the data including a first and second plurality of variables;
 wherein a first plurality of variables is associated with one entity of a plurality of entities in a position of a plurality of positions; 
 wherein a second plurality of variables is associated with a performance metric of a plurality of performance metrics associated with the each of the plurality of entities; 
 wherein the plurality of disparate data sources includes at least one of: one or more input datasets, one or more second input datasets, individual performance monitoring, team monitoring, and market monitoring; 
   generating a plurality of indexes, where the plurality of indexes comprises:
 a first index associated with the plurality of positions; 
 a second index associated with the plurality of entities; 
 a third index associated with one or more characteristics associated with each of the plurality of entities; and 
 a fourth index for each of the plurality of performance metrics; 
   storing the plurality of indexes in a database;   extracting one or more associations from the plurality of indexes, wherein each of the one or more associations includes one or more probabilistic distributions based on a relationship between each of the plurality of performance metrics and each of the plurality of positions;   generating, based on each of the plurality of entities and the associated performance metrics, a flight index for each of the entities;   generating, based on each of the plurality of entities and the associated performance metrics, a performance index to each of the entities;
 wherein the flight index is a statistical measure of a likelihood that the associated entity will change from the associated entity's current position within an organization to one or more new positions outside of the organization; 
   comparing the flight index for each of the entities with the performance index of the same entity; and   identifying, based on the comparison, a flight probability of one or more chosen entities of the plurality of entities being higher than a threshold flight probability;   implementing, based on the identification, one or more changes to one or more policies of the organization;
 wherein the one or more changes to one or more policies are configured to reduce the statistical likelihood that the one or more chosen entities will change from a current positions of the one or more chosen entities current position within the organization to one or more new positions outside of the organization; and 
   monitoring, based on the implementation, the flight index of the one or more chosen entities over a period of time.   
     
     
         9 . The method of  claim 8 , the extracting the one or more associations further comprises:
 identifying one or more indicia related to the at least one of: one or more input datasets, one or more second input datasets, individual performance monitoring, team monitoring, and market monitoring; and   wherein the one or more indicia are associated historical conditions related to employee turnover.   
     
     
         10 . The method of  claim 9 , the method further comprising:
 creating a distribution of flight probability for each of the plurality of positions, wherein the distribution uses the generated flight index for each entity of the plurality of entities; and   generating, using the distribution, a quantity of identified entities having a flight index higher than a threshold flight probability in each of the plurality of positions over a duration of time; and   extracting, based on the generation and the third index, a characteristic flight probability metric.   
     
     
         11 . The method of  claim 10 , the method further comprising generating a visualization of the distribution. 
     
     
         12 . The method of  claim 8 , the method further comprising:
 generating a graphical user interface containing information entry fields for receiving user input regarding input datasets;   providing the graphical user interface for display on a user device;   receiving, from the graphical user interface via the user device, the one or more input datasets; and   generating the third index based on the one or more input datasets.   
     
     
         13 . The method of  claim 12 , the method further comprising:
 receiving, from communications between each of the plurality of entities, the one or more input second datasets; and   generating the third index based on the one or more second input datasets.   
     
     
         14 . The method of  claim 10 , wherein the one or more characteristics of the third index includes one or more of the following: commute time, years in an associated position in an organization, time spent at team building events, messages sent within the organization, age, gender, race, sexual orientation, and marital status. 
     
     
         15 . A system comprising:
 a memory storing instructions; and   a processor configured to execute the stored instructions to:
 receive data from a plurality of disparate data sources, the data including a first and second plurality of variables,
 wherein a first plurality of variables is associated with one entity of a plurality of entities in a position of a plurality of positions; 
 wherein a second plurality of variables is associated with a performance metric of a plurality of performance metrics associated with the each of the plurality of entities; 
 
 wherein the plurality of disparate data sources includes at least one of: one or more input datasets, one or more second input datasets, individual performance monitoring, team monitoring, and market monitoring; 
 generate a plurality of indexes, where the plurality of indexes comprises:
 a first index associated with the plurality of positions; 
 a second index associated with the plurality of entities; 
 a third index associated with one or more characteristics associated with each of the plurality of entities; and 
 a fourth index for each of the plurality of performance metrics; 
 
 store the plurality of indexes in a database; 
 extracting one or more associations from the plurality of indexes, wherein each of the one or more associations includes one or more probabilistic distributions based on a relationship between each of the plurality of performance metrics and each of the plurality of positions; 
 generating, based on each of the plurality of entities and the associated performance metrics, a flight index for each of the entities; 
 generating, based on each of the plurality of entities and the associated performance metrics, a performance index to each of the entities;
 wherein the flight index is a statistical measure of a likelihood that the associated entity will change from the associated entity's current position within an organization to one or more new positions outside of the organization; 
 
 comparing the flight index for each of the entities with the performance index of the same entity; and 
 identify, based on the comparison, a flight probability of one or more chosen entities of the plurality of entities being higher than a threshold flight probability; 
   implementing, based on the identification, one or more changes to one or more policies of the organization;
 wherein the one or more changes to one or more policies are configured to reduce the statistical likelihood that the one or more chosen entities will change from a current positions of the one or more chosen entities current position within the organization to one or more new positions outside of the organization; and 
   monitoring, based on the implementation, the flight index of the one or more chosen entities over a period of time.   
     
     
         16 . The system of  claim 15 , wherein extracting the one or more associations further comprises:
 identifying one or more indicia related to the at least one of: one or more input datasets, one or more second input datasets, individual performance monitoring, team monitoring, and market monitoring; and   wherein the one or more indicia are associated historical conditions related to manger performance or employee turnover.   
     
     
         17 . The system of  claim 16 , wherein the processor is further configured to:
 create a distribution of flight probability for each of the plurality of positions, wherein the distribution uses the generated flight index for each entity of the plurality of entities; and   generate, using the distribution, a quantity of identified entities having a flight index higher than a threshold flight probability in each of the plurality of positions over a duration of time; and   extract, based on the generation and the third index, a characteristic flight probability metric.   
     
     
         18 . The system of  claim 17 , wherein the processor is further configured to generate a visualization of the distribution. 
     
     
         19 . The system of  claim 16 , wherein the processor is further configured to:
 generate a graphical user interface containing information entry fields for receiving user input regarding input datasets;   provide the graphical user interface for display on a user device;   receive, from the graphical user interface via the user device, the one or more input datasets; and   generate the third index based on the one or more input datasets.   
     
     
         20 . The system of  claim 19 , wherein the processor is further configured to:
 receive, from communications between each of the plurality of entities, the one or more input second datasets; and   generate the third index based on the one or more second input datasets.   
     
     
         21 .- 54 . (canceled)